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486b1402
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com.unity.ml-agents_1.0.0
com.unity.ml-agents_1.0.2
com.unity.ml-agents_1.0.3
com.unity.ml-agents_1.0.4
com.unity.ml-agents_1.0.5
com.unity.ml-agents_1.0.6
com.unity.ml-agents_1.0.7
com.unity.ml-agents_1.0.8
com.unity.ml-agents_1.1.0
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com.unity.ml-agents_1.3.0
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com.unity.ml-agents_1.6.0
com.unity.ml-agents_1.7.0
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com.unity.ml-agents_1.8.0
com.unity.ml-agents_1.8.1
com.unity.ml-agents_1.9.0
com.unity.ml-agents_1.9.1
com.unity.ml-agents_2.0.0
com.unity.ml-agents_2.1.0
latest_release
python-packages_0.16.0
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v0.1
6 次代码提交 (486b1402-26f8-4515-9825-d60090f9ef53)
| 作者 | SHA1 | 备注 | 提交日期 |
|---|---|---|---|
bhh
|
59933799 | Worm dynamic scene ready | 5 年前 |
|
bhh
|
dc9fcd46 | loosened joints retrained looking good | 5 年前 |
|
bhh
|
58354f1b | updated dynamic 3.5M model | 5 年前 |
GitHub
|
05d80169 | Re-train models for example scenes (#4106) | 5 年前 |
|
GitHub
|
7852bc20 | Update NN files for the release. (#4353) | 4 年前 |
|
GitHub
|
cc10cd82 |
Worm Ragdoll & Env Updates (#4413)
* add worm updates * add rewman * cp * normalize rewards * only cookie * try 20M. Add3.5Mnn file * reduce strength to 3000spring * facing reward troubleshooting * Update WormAgent.cs * troubleshoot nan * try product of rewards * train 5M steps * try end episode on target touch * fix joint obsv * use 7M steps * added nn file for observation joint fix. looks great * don't end episode * remove old code * refactor to patterns used in walker & crawler * add auto-setup code * reformat * use head vel * remove unneeded observ. update prefabs * update static scenes * keeps rolling. added debug. try 5 m/s * gate the facing reward based on angle tolerance * added 10ms_angle30rew_nn files * use fromto rot * use 7M steps * add new trained files. cleanup code and prefabs * use avgvel. add code comments * remove unused method * add more comments * Update Learning-E... |
4 年前 |